Update README.md

README.md

@@ -1,3 +1,50 @@
 ---
 license: mit
+language:
+- ja
 ---
+
+
+# Overview
+
+This model generates text like viewer comments in live streaming, such as Youtube Live.
+
+This model was trained on [rinna/japanese-gpt-neox-3.6b-instruction-ppo](https://huggingface.co/rinna/japanese-gpt-neox-3.6b-instruction-ppo) using Lora.
+
+# How to use the model
+
+~~~~python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("rinna/japanese-gpt-neox-3.6b-instruction-ppo", use_fast=False)
+model = AutoModelForCausalLM.from_pretrained("rinna/japanese-gpt-neox-3.6b-instruction-ppo", torch_dtype=torch.float16, device_map="auto")
+
+from peft import PeftModel
+peft_model = PeftModel.from_pretrained(model, "oshizo/comment-generation-japanese-3.6b-lora", device_map="auto")
+
+
+prompt = f"ユーザー: 今朝うちの小さな畑でトマトがね、いい感じに赤くなってたんだよね。そのまま通学路を歩いてたんだけどさ、一つちぎって弁当に入れておけば良かっな～と思って。トマト可愛くて好き。<NL>システム: "
+token_ids = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt")
+
+with torch.no_grad():
+    output_ids = model.generate(
+        token_ids.to(model.device),
+        do_sample=True,
+        max_new_tokens=32,
+        num_return_sequences=4,
+        pad_token_id=tokenizer.pad_token_id,
+        bos_token_id=tokenizer.bos_token_id,
+        eos_token_id=tokenizer.eos_token_id
+    )
+for output in output_ids.tolist():
+    print(tokenizer.decode(output[token_ids.size(1):], skip_special_tokens=True))
+
+# これから剥くの面倒くさいよ<NL>
+# なんやその可愛い好きは<NL>
+# 冷やしておくと美味しいよな<NL>
+# 食レポ具体的に<NL>
+~~~~
+
+
+